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[MRG+1] Fix Error: 'MultiTaskLasso' object has no attribute 'coef_' when warm_start = True #12361

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Merged
merged 3 commits into from
Oct 21, 2018
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[MRG+1] Fix Error: 'MultiTaskLasso' object has no attribute 'coef_' when warm_start = True #12361

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525db2b
update to fix .coef_ issue for MultiTaskLasso
joaak Oct 12, 2018
94ad80e
add non-regression test for MultiTaskLasso with warm_start = True
joaak Oct 14, 2018
16dc49d
add fix for MultiTaskLasso with warm_start = True
joaak Oct 15, 2018
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6 changes: 6 additions & 0 deletions doc/whats_new/v0.21.rst
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Expand Up @@ -40,6 +40,12 @@ Support for Python 3.4 and below has been officially dropped.
- An entry goes here
- An entry goes here

:mod:`sklearn.linear_model`
...........................
- |Fix| Fixed a bug in :class:`linear_model.MultiTaskElasticNet` which was breaking
``MultiTaskElasticNet`` and ``MultiTaskLasso`` when ``warm_start = True``. :issue:`12360`
by :user:`Aakanksha Joshi <joaak>`.

:mod:`sklearn.cluster`
......................

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2 changes: 1 addition & 1 deletion sklearn/linear_model/coordinate_descent.py
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Expand Up @@ -1795,7 +1795,7 @@ def fit(self, X, y):
X, y, X_offset, y_offset, X_scale = _preprocess_data(
X, y, self.fit_intercept, self.normalize, copy=False)

if not self.warm_start or self.coef_ is None:
if not self.warm_start or not hasattr(self, "coef_"):
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Just to be safe, we might want to handle the case where coef_ is None in case someone relied on this broken implementation...?

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Maybe this condition

Suggested change
if not self.warm_start or not hasattr(self, "coef_"):
if not self.warm_start or not hasattr(self, "coef_") or self.coef_ is None:

should be able to handle that?

self.coef_ = np.zeros((n_tasks, n_features), dtype=X.dtype.type,
order='F')

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12 changes: 12 additions & 0 deletions sklearn/linear_model/tests/test_coordinate_descent.py
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Expand Up @@ -818,3 +818,15 @@ def test_coef_shape_not_zero():
est_no_intercept = Lasso(fit_intercept=False)
est_no_intercept.fit(np.c_[np.ones(3)], np.ones(3))
assert est_no_intercept.coef_.shape == (1,)


def test_warm_start_multitask_lasso():
X, y, X_test, y_test = build_dataset()
Y = np.c_[y, y]
clf = MultiTaskLasso(alpha=0.1, max_iter=5, warm_start=True)
ignore_warnings(clf.fit)(X, Y)
ignore_warnings(clf.fit)(X, Y) # do a second round with 5 iterations

clf2 = MultiTaskLasso(alpha=0.1, max_iter=10)
ignore_warnings(clf2.fit)(X, Y)
assert_array_almost_equal(clf2.coef_, clf.coef_)